# coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

r"""Ground truth values for `german_credit_numeric_sparse_logistic_regression`."""

import numpy as np

PARAMS_MEAN: np.ndarray = np.array([
    -1.1866850128770667,
    1.0380728657404157,
    -1.0068486780018866,
    0.3978288786750602,
    -0.9767080480077827,
    -0.6362924890325236,
    -0.6051996728301182,
    0.006105139365094615,
    0.6609658434140852,
    -0.4249951910065505,
    -0.7954538335475692,
    0.3315770431374626,
    0.046985122992208625,
    -0.34935398006844903,
    -0.8195538641091478,
    0.8956062666219922,
    -0.8829364341740176,
    0.6781056103783146,
    0.6268106971402724,
    0.4594701341100028,
    -0.39557662134638816,
    -0.19096731751483484,
    -0.030070921060829498,
    1.4541849438486162e-05,
    -1.3476546124139996,
    2.4711169992301327,
    1.7894534236627444,
    1.656054003383698,
    0.5507912750655815,
    1.5411862565439534,
    0.7635904955673258,
    0.7028700409415611,
    0.34032760037885834,
    0.8306040538526964,
    0.5407597178919572,
    0.9945344325618312,
    0.46716848631969565,
    0.3341256120446421,
    0.4682846990858353,
    1.116661964897736,
    1.247227828047238,
    1.249637888081319,
    0.904102372009462,
    0.8210224420155694,
    0.6212448784986447,
    0.5841921098136925,
    0.3694212194004735,
    0.3534317426396826,
    0.34832304680340564,
    3.2923218637066674,
    0.3464495946024001,
]).reshape((51,))

PARAMS_MEAN_STANDARD_ERROR: np.ndarray = np.array([
    0.00066315417083035,
    0.0006701121920605211,
    0.0006316481592457246,
    0.0009113113044432006,
    0.0006474416872517981,
    0.0008924040168406635,
    0.0008503675033556548,
    0.0007741822280038785,
    0.0008570802267868499,
    0.0008304841879993428,
    0.0007679569816334657,
    0.0008141135814107538,
    0.0008133538366162509,
    0.0007925501556716537,
    0.0007891118121214018,
    0.0006926806961572863,
    0.0006776803166247707,
    0.0009181852420520739,
    0.0009458251891323173,
    0.0008753925086083088,
    0.0008808549357175388,
    0.0008380834058704306,
    0.0007399676887010606,
    0.0008050510286215137,
    0.0006811946760921953,
    0.0018189143305716187,
    0.0015616348064017452,
    0.0013486961486267783,
    0.0007846612904802629,
    0.0013444773323028454,
    0.0010219869940686157,
    0.0009838605522402807,
    0.0005734833543596508,
    0.0010692095314710625,
    0.0008141779830663896,
    0.0011923924131738194,
    0.0007929590422675487,
    0.0005970173509868335,
    0.0007723467580812496,
    0.0012461443855807971,
    0.0012407036866404343,
    0.0011956318941933775,
    0.0013479930763519422,
    0.001283742995985739,
    0.0008712592615699043,
    0.0009000221658965747,
    0.0006218172297989711,
    0.0006594805268774455,
    0.00060125330054623,
    0.0023402267517388985,
    0.0002826803690944519,
]).reshape((51,))

PARAMS_STANDARD_DEVIATION: np.ndarray = np.array([
    0.5695238528749824,
    0.5622316913857365,
    0.5597765649148352,
    0.788923364728517,
    0.5609660396029171,
    0.6915327091638241,
    0.6975121652807991,
    0.8203962385547783,
    0.6906283355471844,
    0.7675948990181268,
    0.6048973750396965,
    0.7910139572493385,
    0.817705862531961,
    0.7828471009029198,
    0.6210279443757918,
    0.5692037299715765,
    0.5865585683824852,
    0.6991723672273238,
    0.7185456547238539,
    0.7741124868680267,
    0.7972600278141689,
    0.8049623498995004,
    0.8220256297068674,
    0.820983228874157,
    0.5770904899564452,
    1.5187235240763841,
    1.2986300854078803,
    1.2382447236552543,
    0.8071753755402582,
    1.2024498058790793,
    0.9235582496964273,
    0.8830151651146133,
    0.6158863871703063,
    0.9681792162412519,
    0.7937895494791374,
    1.0058932841404686,
    0.7397321783895701,
    0.6084990377842512,
    0.7416667756268222,
    1.092559628333138,
    1.096040508222368,
    1.1215307396947414,
    1.0355073577446263,
    0.9755585380196552,
    0.8489758089778293,
    0.83429162115973,
    0.6452778031812687,
    0.6284495013260469,
    0.6231562408813887,
    1.7701592484592346,
    0.14778162108982326,
]).reshape((51,))
